fix(v2): weighted 零权重测试改确定性断言(去抽样偏置)——套件回绿
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_013nMthbVEmQquxBRKb9Fj8u
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@@ -42,15 +42,39 @@ func TestWeightedDistributesAndRespectsWeight(t *testing.T) {
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}
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}
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// TestWeightedZeroWeightTreatedAsOne 用确定性断言(非抽样分布)验证 Weight<=0 记 1。
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//
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// 此前版本靠 400 个 "N<digit><letter>"(i%10, i%26 联动生成)key 抽样统计两账户
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// 是否都出现过 —— 但 fnv32a 对这批同构 key 恰好全部落在偶数哈希(见 check.go 复现),
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// 导致抽样必然只命中一侧、测试恒红,与实现无关(已用随机 key / 完整 10x26 网格核实
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// 实现对普通 key 分布均匀,证据见修复报告)。改为:
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// 1. 单候选 weight=0 必须可选中(不因权重被当成 0 而排除)。
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// 2. 两候选 weight=0+0 → 各按文档规则记 1、总权重 2,target=fnv32a(key)%2,
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// 按候选顺序累加桶(a1 占 [0,1)、a2 占 [1,2))。用两个已知奇偶性的字面量 key
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// (提前用同一 fnv32a 规则手算)分别断言恰好落在 a1 / a2,不依赖分布采样。
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func TestWeightedZeroWeightTreatedAsOne(t *testing.T) {
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w := accounts.NewWeighted()
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cs := []config.AccountConfig{{AccountID: "a1", Weight: 0}, {AccountID: "a2", Weight: 0}}
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counts := map[string]int{}
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for i := 0; i < 400; i++ {
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got, _ := w.Pick("fake|global", cs, accounts.PickHint{OutTradeNo: "N" + string(rune('0'+i%10)) + string(rune('a'+i%26))})
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counts[got.AccountID]++
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single := []config.AccountConfig{{AccountID: "solo", Weight: 0}}
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got, err := w.Pick("fake|global", single, accounts.PickHint{OutTradeNo: "ANY-KEY"})
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if err != nil || got.AccountID != "solo" {
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t.Fatalf("单候选 weight=0 应可选中, got %v err %v", got, err)
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}
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if counts["a1"] == 0 || counts["a2"] == 0 {
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t.Fatalf("weight=0 应当 1 处理、两账户都可选, got %+v", counts)
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cs := []config.AccountConfig{{AccountID: "a1", Weight: 0}, {AccountID: "a2", Weight: 0}}
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// fnv32a("PAY-0002") = 3179067314,偶数 → target=0,落 a1 的 [0,1) 桶。
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// fnv32a("PAY-0001") = 3162289695,奇数 → target=1,落 a2 的 [1,2) 桶。
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cases := []struct {
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key string
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want string
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}{
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{"PAY-0002", "a1"},
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{"PAY-0001", "a2"},
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}
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for _, tc := range cases {
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got, err := w.Pick("fake|global", cs, accounts.PickHint{OutTradeNo: tc.key})
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if err != nil || got.AccountID != tc.want {
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t.Fatalf("key=%s: weight=0 应按 1 处理走桶, want %s got %v err %v", tc.key, tc.want, got, err)
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}
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}
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}
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